Sensor devices can measure and inspect items conveyed along the production line (hereafter, work piece(s)), and are thus quite popular in factory automation (FA). These sensor devices are typically referred to as image sensors or visual sensors. The image sensor may be configured from a camera and an image processing device, and matches a preliminarily registered teaching object (also known as a model or pattern) to detect a work piece in an image and further extract the required information or perform a measurement. The output from the image sensor may be used for various purposes, such as recognizing, inspecting, or sorting the work pieces.
An increasingly popular production format in FA involves conveying a plurality of different types of work pieces mixed together on the same line and apply different kinds of processes based on the type of work piece. For instance, different types of work pieces flow randomly via a conveyor on a production line for packaging an assortment of products. Picker robots then pick up, correctly position, and pack the different categories of work pieces. Furthermore, a high-variety low-volume line can manufacture a product series where the specifications such as the shape, color, size of the work pieces differ slightly; here, the processing method, inspection requirements, or the like may differ for each specification.
Recognizing (as well as detecting or searching) for a plurality of models from an image is necessary on a line flowing a mix of a plurality of different types of work pieces (hereafter, “mixed flow production line”). Objects may be recognized using a single model. In this case, to shorten the processing time, reduce the memory usage, and improve accuracy, a model image is decimated to generate a model template. The input image is decimated using the same reduction ratio as the model template and the search takes place using the reduced input image (refer to Patent Document 1). This technique is particularly effective for registered models with large image data. The reduction ratio may be determined so that the number of feature points contained in the model is a predetermined number of feature points, or may be determined so that the area of a registered region is a predetermined size.
Since a plurality of models need to be recognized on a mixed flow production line, the above-mentioned search process must be repeated for the number of models. Accordingly, the processing time increases as the number of models grows.
Another method uses multi-resolution images (i.e., an image pyramid) to detect an object. This method establishes a reduction ratio b for a template, b=aN, where a, is the reduction ratio of the pyramid image, and N is an integer greater than or equal to 2 (refer to Patent Document 2). The method reduces the number of pyramid images and the number of templates used for matching, and thereby improves the speed of the detection process. However this method is unsuitable when the objects for detection are of different types.